Heuristic reasoning about uncertainty: an artificial intelligence approach
Heuristic reasoning about uncertainty: an artificial intelligence approach
Control metaphors in the modelling of economic learning and decision-making behaviour
Computational Economics
Computer science as empirical inquiry: symbols and search
Communications of the ACM
Simulation for the Social Scientist
Simulation for the Social Scientist
SDML: A Multi-Agent Language for Organizational Modelling
Computational & Mathematical Organization Theory
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Two-Phase Distributed Observation Problems
ACSD '05 Proceedings of the Fifth International Conference on Application of Concurrency to System Design
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This work describes an agent-based model of an organisation. The model is made of workers, which are assigned tasks that have to be solved by analyzing some information items. Information quality has been modelled by associating to each item a probability of being wrong. Workers can interact with each other to recommend information items. During the simulations, we have induced deep reorganisation by changing the quality of the information items, inducing strong structural change. We have experimented with different information seeking behaviour for the workers and analyzed organisation performance, group formation and structural change in the periods of strong change.